Sequential pattern mining

Research output: Contribution to report/book/conference proceedingsChapter

Authors

  • Da Ruan
  • Tian-Rui Li
  • Yang Xu
  • Wu-ming Pan

Institutes & Expert groups

Documents & links

Abstract

Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous research is mainly focused on investigating scalable algorithms for mining sequential patterns while less on its theoretical foundations. However, the latter is also important because it can help to use existing theories and methods to support more effective mining tasks. In this chapter, we onduct a systematic study on models and algorithms in sequential pattern analysis, especially discuss the existing algorithms' advantages and limitations. Then, we build the relation between the closed sequential patterns and fixed point, which can serve as a theoretical foundation of sequential patterns. Finally, we discuss its applications and outline the future research work.

Details

Original languageEnglish
Title of host publicationIntelligent Data Mining - Techniques and Applications
Place of PublicationHeidelberg
PublisherSpringer
Pages103-122
Volume1
Edition1
ISBN (Print)978-3-540-26256-5
Publication statusPublished - Aug 2005

Keywords

  • data mining, sequential pattern, web intelligence

ID: 114992